





import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter

import requests


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__							,lowerCAmelCase__=None						):
		lowerCamelCase_	:     str 						=      None
		if token is not None:
				lowerCamelCase_	:     List[str] 						=      {"Accept": "application/vnd.github+json", "Authorization": F"Bearer {token}"}

		lowerCamelCase_	:     Optional[int] 						=      F"https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100"
		lowerCamelCase_	:     Optional[int] 						=      requests.get(_lowerCamelCase							,headers=_lowerCamelCase						).json()
		lowerCamelCase_	:     Optional[Any] 						=      {}

		try:
				job_links.update({job['name']: job['html_url'] for job in result['jobs']}						)
				lowerCamelCase_	:     List[str] 						=      math.ceil((result['total_count'] - 1_00) / 1_00						)

				for i in range(_lowerCamelCase						):
						lowerCamelCase_	:     Dict 						=      requests.get(url + F"&page={i + 2}"							,headers=_lowerCamelCase						).json()
						job_links.update({job['name']: job['html_url'] for job in result['jobs']}						)

				return job_links
		except Exception:
				print(F"Unknown error, could not fetch links:\n{traceback.format_exc()}"						)

		return {}


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__							,lowerCAmelCase__=None						):
		lowerCamelCase_	:     Dict 						=      None
		if token is not None:
				lowerCamelCase_	:     Any 						=      {"Accept": "application/vnd.github+json", "Authorization": F"Bearer {token}"}

		lowerCamelCase_	:     Dict 						=      F"https://api.github.com/repos/huggingface/transformers/actions/runs/{worflow_run_id}/artifacts?per_page=100"
		lowerCamelCase_	:     List[str] 						=      requests.get(_lowerCamelCase							,headers=_lowerCamelCase						).json()
		lowerCamelCase_	:     Union[str, Any] 						=      {}

		try:
				artifacts.update({artifact['name']: artifact['archive_download_url'] for artifact in result['artifacts']}						)
				lowerCamelCase_	:     Union[str, Any] 						=      math.ceil((result['total_count'] - 1_00) / 1_00						)

				for i in range(_lowerCamelCase						):
						lowerCamelCase_	:     Any 						=      requests.get(url + F"&page={i + 2}"							,headers=_lowerCamelCase						).json()
						artifacts.update({artifact['name']: artifact['archive_download_url'] for artifact in result['artifacts']}						)

				return artifacts
		except Exception:
				print(F"Unknown error, could not fetch links:\n{traceback.format_exc()}"						)

		return {}


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__							,lowerCAmelCase__							,lowerCAmelCase__							,lowerCAmelCase__						):
		lowerCamelCase_	:     Optional[int] 						=      None
		if token is not None:
				lowerCamelCase_	:     Tuple 						=      {"Accept": "application/vnd.github+json", "Authorization": F"Bearer {token}"}

		lowerCamelCase_	:     Optional[Any] 						=      requests.get(_lowerCamelCase							,headers=_lowerCamelCase							,allow_redirects=_lowerCamelCase						)
		lowerCamelCase_	:     str 						=      result.headers["Location"]
		lowerCamelCase_	:     Optional[Any] 						=      requests.get(_lowerCamelCase							,allow_redirects=_lowerCamelCase						)
		lowerCamelCase_	:     Any 						=      os.path.join(_lowerCamelCase							,F"{artifact_name}.zip"						)
		with open(_lowerCamelCase							,'wb'						) as fp:
				fp.write(response.content						)


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__							,lowerCAmelCase__=None						):
		lowerCamelCase_	:     str 						=      []
		lowerCamelCase_	:     List[Any] 						=      []
		lowerCamelCase_	:     Union[str, Any] 						=      None

		with zipfile.ZipFile(_lowerCamelCase						) as z:
				for filename in z.namelist():
						if not os.path.isdir(_lowerCamelCase						):
								# read the file
								if filename in ["failures_line.txt", "summary_short.txt", "job_name.txt"]:
										with z.open(_lowerCamelCase						) as f:
												for line in f:
														lowerCamelCase_	:     Union[str, Any] 						=      line.decode('UTF-8'						).strip()
														if filename == "failures_line.txt":
																try:
																		# `error_line` is the place where `error` occurs
																		lowerCamelCase_	:     Dict 						=      line[: line.index(': '						)]
																		lowerCamelCase_	:     List[Any] 						=      line[line.index(': '						) + len(': '						) :]
																		errors.append([error_line, error]						)
																except Exception:
																		# skip un-related lines
																		pass
														elif filename == "summary_short.txt" and line.startswith('FAILED '						):
																# `test` is the test method that failed
																lowerCamelCase_	:     Tuple 						=      line[len('FAILED '						) :]
																failed_tests.append(_lowerCamelCase						)
														elif filename == "job_name.txt":
																lowerCamelCase_	:     Dict 						=      line

		if len(_lowerCamelCase						) != len(_lowerCamelCase						):
				raise ValueError(
				    F"`errors` and `failed_tests` should have the same number of elements. Got {len(_lowerCamelCase						)} for `errors` "
				    F"and {len(_lowerCamelCase						)} for `failed_tests` instead. The test reports in {artifact_zip_path} have some"
				    ' problem.'						)

		lowerCamelCase_	:     Optional[Any] 						=      None
		if job_name and job_links:
				lowerCamelCase_	:     Union[str, Any] 						=      job_links.get(_lowerCamelCase							,_lowerCamelCase						)

		# A list with elements of the form (line of error, error, failed test)
		lowerCamelCase_	:     int 						=      [x + [y] + [job_link] for x, y in zip(_lowerCamelCase							,_lowerCamelCase						)]

		return result


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__							,lowerCAmelCase__=None						):
		lowerCamelCase_	:     Any 						=      []

		lowerCamelCase_	:     Dict 						=      [os.path.join(_lowerCamelCase							,_lowerCamelCase						) for p in os.listdir(_lowerCamelCase						) if p.endswith('.zip'						)]
		for p in paths:
				errors.extend(get_errors_from_single_artifact(_lowerCamelCase							,job_links=_lowerCamelCase						)						)

		return errors


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__							,lowerCAmelCase__=None						):
		lowerCamelCase_	:     Union[str, Any] 						=      Counter()
		counter.update([x[1] for x in logs]						)
		lowerCamelCase_	:     Tuple 						=      counter.most_common()
		lowerCamelCase_	:     List[Any] 						=      {}
		for error, count in counts:
				if error_filter is None or error not in error_filter:
						lowerCamelCase_	:     Tuple 						=      {"count": count, "failed_tests": [(x[2], x[0]) for x in logs if x[1] == error]}

		lowerCamelCase_	:     Optional[int] 						=      dict(sorted(r.items()							,key=lambda lowerCAmelCase__						: item[1]["count"]							,reverse=_lowerCamelCase						)						)
		return r


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__						):
		lowerCamelCase_	:     List[Any] 						=      test.split('::'						)[0]
		if test.startswith('tests/models/'						):
				lowerCamelCase_	:     Union[str, Any] 						=      test.split('/'						)[2]
		else:
				lowerCamelCase_	:     int 						=      None

		return test


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__							,lowerCAmelCase__=None						):
		lowerCamelCase_	:     List[str] 						=      [(x[0], x[1], get_model(x[2]						)) for x in logs]
		lowerCamelCase_	:     List[Any] 						=      [x for x in logs if x[2] is not None]
		lowerCamelCase_	:     Optional[Any] 						=      {x[2] for x in logs}

		lowerCamelCase_	:     str 						=      {}
		for test in tests:
				lowerCamelCase_	:     Union[str, Any] 						=      Counter()
				# count by errors in `test`
				counter.update([x[1] for x in logs if x[2] == test]						)
				lowerCamelCase_	:     int 						=      counter.most_common()
				lowerCamelCase_	:     Union[str, Any] 						=      {error: count for error, count in counts if (error_filter is None or error not in error_filter)}
				lowerCamelCase_	:     Union[str, Any] 						=      sum(error_counts.values()						)
				if n_errors > 0:
						lowerCamelCase_	:     str 						=      {"count": n_errors, "errors": error_counts}

		lowerCamelCase_	:     int 						=      dict(sorted(r.items()							,key=lambda lowerCAmelCase__						: item[1]["count"]							,reverse=_lowerCamelCase						)						)
		return r


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__						):
		lowerCamelCase_	:     Union[str, Any] 						=      "| no. | error | status |"
		lowerCamelCase_	:     Any 						=      "|-:|:-|:-|"
		lowerCamelCase_	:     Tuple 						=      [header, sep]
		for error in reduced_by_error:
				lowerCamelCase_	:     Optional[int] 						=      reduced_by_error[error]["count"]
				lowerCamelCase_	:     Optional[Any] 						=      F"| {count} | {error[:1_00]} |  |"
				lines.append(_lowerCamelCase						)

		return "\n".join(_lowerCamelCase						)


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__						):
		lowerCamelCase_	:     str 						=      "| model | no. of errors | major error | count |"
		lowerCamelCase_	:     int 						=      "|-:|-:|-:|-:|"
		lowerCamelCase_	:     Optional[int] 						=      [header, sep]
		for model in reduced_by_model:
				lowerCamelCase_	:     List[str] 						=      reduced_by_model[model]["count"]
				lowerCamelCase_	:     Union[str, Any] 						=      list(reduced_by_model[model]['errors'].items()						)[0]
				lowerCamelCase_	:     Union[str, Any] 						=      F"| {model} | {count} | {error[:60]} | {_count} |"
				lines.append(_lowerCamelCase						)

		return "\n".join(_lowerCamelCase						)


if __name__ == "__main__":
		_lowercase		:  Any			       =argparse.ArgumentParser()
		# Required parameters
		parser.add_argument("""--workflow_run_id""", type=str, required=True, help="""A GitHub Actions workflow run id.""")
		parser.add_argument(
		    """--output_dir""",
		    type=str,
		    required=True,
		    help="""Where to store the downloaded artifacts and other result files.""",
		)
		parser.add_argument("""--token""", default=None, type=str, help="""A token that has actions:read permission.""")
		_lowercase		:  List[Any]			       =parser.parse_args()

		os.makedirs(args.output_dir, exist_ok=True)

		_lowercase		:  Tuple			       =get_job_links(args.workflow_run_id, token=args.token)
		_lowercase		:  List[Any]			       ={}
		# To deal with `workflow_call` event, where a job name is the combination of the job names in the caller and callee.
		# For example, `PyTorch 1.11 / Model tests (models/albert, single-gpu)`.
		if _job_links:
				for k, v in _job_links.items():
						# This is how GitHub actions combine job names.
						if " / " in k:
								_lowercase		:  Tuple			       =k.find(""" / """)
								_lowercase		:  Union[str, Any]			       =k[index + len(""" / """) :]
						_lowercase		:  Union[str, Any]			       =v
		with open(os.path.join(args.output_dir, """job_links.json"""), """w""", encoding="""UTF-8""") as fp:
				json.dump(job_links, fp, ensure_ascii=False, indent=4)

		_lowercase		:  List[str]			       =get_artifacts_links(args.workflow_run_id, token=args.token)
		with open(os.path.join(args.output_dir, """artifacts.json"""), """w""", encoding="""UTF-8""") as fp:
				json.dump(artifacts, fp, ensure_ascii=False, indent=4)

		for idx, (name, url) in enumerate(artifacts.items()):
				download_artifact(name, url, args.output_dir, args.token)
				# Be gentle to GitHub
				time.sleep(1)

		_lowercase		:  List[str]			       =get_all_errors(args.output_dir, job_links=job_links)

		# `e[1]` is the error
		_lowercase		:  Union[str, Any]			       =Counter()
		counter.update([e[1] for e in errors])

		# print the top 30 most common test errors
		_lowercase		:  str			       =counter.most_common(30)
		for item in most_common:
				print(item)

		with open(os.path.join(args.output_dir, """errors.json"""), """w""", encoding="""UTF-8""") as fp:
				json.dump(errors, fp, ensure_ascii=False, indent=4)

		_lowercase		:  Dict			       =reduce_by_error(errors)
		_lowercase		:  Any			       =reduce_by_model(errors)

		_lowercase		:  str			       =make_github_table(reduced_by_error)
		_lowercase		:  List[str]			       =make_github_table_per_model(reduced_by_model)

		with open(os.path.join(args.output_dir, """reduced_by_error.txt"""), """w""", encoding="""UTF-8""") as fp:
				fp.write(sa)
		with open(os.path.join(args.output_dir, """reduced_by_model.txt"""), """w""", encoding="""UTF-8""") as fp:
				fp.write(sa)


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


lowercase    :   int						=			{
    'configuration_conditional_detr': [
        'CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'ConditionalDetrConfig',
        'ConditionalDetrOnnxConfig',
    ]
}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase    :   List[str]						=			['ConditionalDetrFeatureExtractor']
		lowercase    :   int						=			['ConditionalDetrImageProcessor']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase    :   Optional[int]						=			[
		    'CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'ConditionalDetrForObjectDetection',
		    'ConditionalDetrForSegmentation',
		    'ConditionalDetrModel',
		    'ConditionalDetrPreTrainedModel',
		]


if TYPE_CHECKING:
		from .configuration_conditional_detr import (
		    CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    ConditionalDetrConfig,
		    ConditionalDetrOnnxConfig,
		)

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_conditional_detr import ConditionalDetrFeatureExtractor
				from .image_processing_conditional_detr import ConditionalDetrImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_conditional_detr import (
				    CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ConditionalDetrForObjectDetection,
				    ConditionalDetrForSegmentation,
				    ConditionalDetrModel,
				    ConditionalDetrPreTrainedModel,
				)

else:
		import sys

		lowercase    :   Optional[int]						=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)